Slightly bizarre request, I know, but bear with me.
I have an Excel spreadsheet with some logging data taken from a highly parallelised bit of server-side code. I'm trying to analyse it for where there may be gaps in the logs, indicating tasks that should be logged but aren't; but because it's a serial, timestamp-order list of a dozen or so parallel threads it's quite hard to read. So I had the unorthodox idea of using a Gantt chart to visualise the overlapping tasks. Excel is terrible at this, so I started looking at alternative tools, and I thought of trying R.
Each task in the log has a start timestamp, and end timestamp, and a duration, so I have the data that I need. I read this SO post and mutilated the example into this R script:
tasks <- c("Task1", "Task2")
dfr <- data.frame(
name = factor(tasks, levels = tasks),
start.date = c("07/08/2013 09:03:25.815", "07/08/2013 09:03:25.956"),
end.date = c("07/08/2013 09:03:28.300", "07/08/2013 09:03:30.409"),
is.critical = c(TRUE, TRUE)
)
mdfr <- melt(dfr, measure.vars = c("start.date", "end.date"))
ggplot(mdfr, aes(as.Date(value, "%d/%m/%Y %H:%M:%OS"), name, colour = is.critical)) +
geom_line(size = 6) +
xlab("") + ylab("") +
theme_bw()
This doesn't work, though -- it doesn't plot any data, and the time axis is all messed up. I suspect (unsurprisingly) that plotting sub-second Gantt charts is a weird thing to do. I'm a complete R newbie (although I've been looking for an excuse to try it out for ages) -- is there any simple way to make this work?